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Mobile Edge Communications, Computing, and Caching(MEC3) Technology in the Maritime Communication Network 认领 引用 被引量：22
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作者 Jie Zeng Jiaying Sun +1 位作者 Binwei Wu Xin Su 《China Communications》 SCIE CSCD 2020年第5期223-234,共12页
With the increasing maritime activities and the rapidly developing maritime economy, the fifth-generation(5G) mobile communication system is expected to be deployed at the ocean. New technologies need to be explored t... With the increasing maritime activities and the rapidly developing maritime economy, the fifth-generation(5G) mobile communication system is expected to be deployed at the ocean. New technologies need to be explored to meet the requirements of ultra-reliable and low latency communications(URLLC) in the maritime communication network(MCN). Mobile edge computing(MEC) can achieve high energy efficiency in MCN at the cost of suffering from high control plane latency and low reliability. In terms of this issue, the mobile edge communications, computing, and caching(MEC3) technology is proposed to sink mobile computing, network control, and storage to the edge of the network. New methods that enable resource-efficient configurations and reduce redundant data transmissions can enable the reliable implementation of computing-intension and latency-sensitive applications. The key technologies of MEC3 to enable URLLC are analyzed and optimized in MCN. The best response-based offloading algorithm(BROA) is adopted to optimize task offloading. The simulation results show that the task latency can be decreased by 26.5’ ms, and the energy consumption in terminal users can be reduced to 66.6%. 展开更多
关键词 best response-based offloading algorithm(BROA) energy consumption mobile edge computing(MEC) mobile edge communications,computing,and caching(MEC3) task offloading
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Beyond 5G Networks: Integration of Communication, Computing, Caching, and Control 认领 引用 被引量：8
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作者 Musbahu Mohammed Adam Liqiang Zhao +1 位作者 Kezhi Wang Zhu Han 《China Communications》 SCIE CSCD 2023年第7期137-174,共38页
In recent years,the exponential proliferation of smart devices with their intelligent applications poses severe challenges on conventional cellular networks.Such challenges can be potentially overcome by integrating c... In recent years,the exponential proliferation of smart devices with their intelligent applications poses severe challenges on conventional cellular networks.Such challenges can be potentially overcome by integrating communication,computing,caching,and control(i4C)technologies.In this survey,we first give a snapshot of different aspects of the i4C,comprising background,motivation,leading technological enablers,potential applications,and use cases.Next,we describe different models of communication,computing,caching,and control(4C)to lay the foundation of the integration approach.We review current stateof-the-art research efforts related to the i4C,focusing on recent trends of both conventional and artificial intelligence(AI)-based integration approaches.We also highlight the need for intelligence in resources integration.Then,we discuss the integration of sensing and communication(ISAC)and classify the integration approaches into various classes.Finally,we propose open challenges and present future research directions for beyond 5G networks,such as 6G. 展开更多
关键词 4C 6G integration of communication,computing,caching,and control i4C multi-access edge computing(MEC)
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Overview of heterogeneous AMN architectures integrating satellite and terrestrial networks:A communication–sensing–computing perspective 认领 引用
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作者 Zhuojia YANG Wei SU Hongke ZHANG 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第5期1-4,共4页
The Airborne Maneuvering Network(AMN)is a novel network architecture that enables flexible deployment across wide areas and provides real-time cross-domain transmission services.Under concurrent and diversified servic... The Airborne Maneuvering Network(AMN)is a novel network architecture that enables flexible deployment across wide areas and provides real-time cross-domain transmission services.Under concurrent and diversified service demands,AMN operating in isolation faces significant challenges in guaranteeing end-to-end transmission reliability.This has prompted the deep integration of AMN with terrestrial and satellite networks to form heterogeneous networks,which has become a crucial trend in improving the continuity and reliability of AMN services.However,network heterogeneity,dynamic resource distribution,and the absence of a unified reliable transmission mechanism impose severe challenges on multi-domain cooperative scheduling and differentiated-service adaptation.This paper serves as a reference for global scholars engaged in thorough research on heterogeneous integrated AMN.It outlines the fundamental characteristics of AMN,reviews recent advances and challenges in communication-sensing-computation coordination,unified control adaptation,and service reliability assurance,and discusses design concepts and future evolution paths for heterogeneous integrated AMN architectures. 展开更多
关键词 Airborne Maneuvering Net-work(AMN) Communication,sensing and computing Heterogeneous integrated network Network architecture Service reliability assurance
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LLM-Enhanced Multi-Agent Transfer Reinforcement Learning for Sensing,Communication,Computing,and Control Co-Optimization in Cyber-Physical Systems 认领 引用
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作者 Junyuan Zhang Chi Xu Haibin Yu 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2026年第5期1251-1253,共3页
Dear Editor,With the rapid development of new-generation information and communication technology,the fusion of sensing,communication,computing,and control(S3C)is becoming increasingly significant for cyber-physical s... Dear Editor,With the rapid development of new-generation information and communication technology,the fusion of sensing,communication,computing,and control(S3C)is becoming increasingly significant for cyber-physical systems(CPS).However,due to the non-convexity,the curse of dimensionality,and the partial observability faced by CPS,traditional convex optimization algorithms are challenging to deal with S3C co-optimization. 展开更多
关键词 computing convex optimization algorithms LLM enhanced reinforcement communication sensing learning multi agent
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Intelligent joint communication and computation scheme of UAV-assisted offloading in high speed rail scenarios 认领 引用 被引量：1
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作者 Xiqi Cheng Jingxuan Zhang +4 位作者 Xiaodong Xu Shujun Han Bizhu Wang Mengyin Sun Ping Zhang 《Digital Communications and Networks》 SCIE EI CSCD 2026年第4期594-606,共13页
With the continuous development of communication and computation technologies, large bandwidth services place higher demands on computing capacity and throughput in High-Speed Rail(HSR) scenarios. On the one hand, Mil... With the continuous development of communication and computation technologies, large bandwidth services place higher demands on computing capacity and throughput in High-Speed Rail(HSR) scenarios. On the one hand, Millimetre-Wave enables high data transmission rates, but leads to high Doppler frequency deviation as well as large path loss. On the other hand, the development of Mobile Edge Computing greatly alleviates user computing congestion. In this paper, we propose the Adaptive Joint Communication and Computation Resource Allocation scheme to solve the energy optimization problem of a dual-band UAV and Mobile Relay relay-assisted HSR offloading system. This scheme works well to optimize the performance of the system through resource allocation. In addition, since the optimization problem is modeled as a Mixed-Integer Nonlinear Program, we propose the Pre-and Post-state connected Parameterized Deep Q-Network algorithm, which is based on Deep Reinforcement Learning approach, for offloading decision and bandwidth resource allocation. Simulation results show that the proposed algorithms result in lower system energy consumption, while ensuring a high task completion rate as well. 展开更多
关键词 Unmanned aerial vehicle relay High-speed rail communication Mobile edge computing Dual-band communication Resource allocation Deep reinforce learning
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Joint Computing and Communication Resource Allocation for Satellite Communication Networks with Edge Computing 认领 引用 被引量：28
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作者 Shanghong Zhang Gaofeng Cui +1 位作者 Yating Long Weidong Wang 《China Communications》 SCIE EI CSCD 2021年第7期236-252,共17页
Benefit from the enhanced onboard processing capacities and high-speed satellite-terrestrial links,satellite edge computing has been regarded as a promising technique to facilitate the execution of the computation-int... Benefit from the enhanced onboard processing capacities and high-speed satellite-terrestrial links,satellite edge computing has been regarded as a promising technique to facilitate the execution of the computation-intensive applications for satellite communication networks(SCNs).By deploying edge computing servers in satellite and gateway stations,SCNs can achieve significant performance gains of the computing capacities at the expense of extending the dimensions and complexity of resource management.Therefore,in this paper,we investigate the joint computing and communication resource management problem for SCNs to minimize the execution latency of the computation-intensive applications,while two different satellite edge computing scenarios and local execution are considered.Furthermore,the joint computing and communication resource allocation problem for the computation-intensive services is formulated as a mixed-integer programming problem.A game-theoretic and many-to-one matching theorybased scheme(JCCRA-GM)is proposed to achieve an approximate optimal solution.Numerical results show that the proposed method with low complexity can achieve almost the same weight-sum latency as the Brute-force method. 展开更多
关键词 satellite communication networks edge computing resource allocation matching theory
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Energy-Efficient Joint Caching and Transcoding for HTTP Adaptive Streaming in 5G Networks with Mobile Edge Computing 认领 引用 被引量：7
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作者 Renchao Xie Zishu Li +2 位作者 Jun Wu Qingmin Jia Tao Huang 《China Communications》 SCIE CSCD 2019年第7期229-244,共16页
With the new promising technique of mobile edge computing (MEC) emerging, by utilizing the edge computing and cloud computing capabilities to realize the HTTP adaptive video streaming transmission in MEC-based 5G netw... With the new promising technique of mobile edge computing (MEC) emerging, by utilizing the edge computing and cloud computing capabilities to realize the HTTP adaptive video streaming transmission in MEC-based 5G networks has been widely studied. Although many works have been done, most of the existing works focus on the issues of network resource utilization or the quality of experience (QoE) promotion, while the energy efficiency is largely ignored. In this paper, different from previous works, in order to realize the energy efficiency for video transmission in MEC-enhanced 5G networks, we propose a joint caching and transcoding schedule strategy for HTTP adaptive video streaming transmission by taking the caching and transcoding into consideration. We formulate the problem of energy-efficient joint caching and transcoding as an integer programming problem to minimize the system energy consumption. Due to solving the optimization problem brings huge computation complexity, therefore, to make the optimization problem tractable, a heuristic algorithm based on simulated annealing algorithm is proposed to iteratively reach the global optimum solution with a lower complexity and higher accuracy. Finally, numerical simulation results are illustrated to demonstrated that our proposed scheme brings an excellent performance. 展开更多
关键词 mobile edge computing HTTP adaptive streaming caching transcoding energy efficiency
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Recent advances in mobile edge computing and content caching 认领 引用 被引量：14
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作者 Sunitha Safavat Naveen Naik Sapavath Danda B.Rawat 《Digital Communications and Networks》 SCIE EI 2020年第2期189-194,共6页
The demand for digital media services is increasing as the number of wireless subscriptions is growing exponentially.In order to meet this growing need,mobile wireless networks have been advanced at a tremendous pace ... The demand for digital media services is increasing as the number of wireless subscriptions is growing exponentially.In order to meet this growing need,mobile wireless networks have been advanced at a tremendous pace over recent days.However,the centralized architecture of existing mobile networks,with limited capacity and range of bandwidth of the radio access network and low bandwidth back-haul network,can not handle the exponentially increasing mobile traffic.Recently,we have seen the growth of new mechanisms of data caching and delivery methods through intermediate caching servers.In this paper,we present a survey on recent advances in mobile edge computing and content caching,including caching insertion and expulsion policies,the behavior of the caching system,and caching optimization based on wireless networks.Some of the important open challenges in mobile edge computing with content caching are identified and discussed.We have also compared edge,fog and cloud computing in terms of delay.Readers of this paper will get a thorough understanding of recent advances in mobile edge computing and content caching in mobile wireless networks. 展开更多
关键词 Mobile edge computing Content caching MEC
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Analysis and Optimization on Partition-Based Caching and Delivery in Satellite-Terrestrial Edge Computing Networks 认领 引用 被引量：4
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作者 Peng Wang Xing Zhang +2 位作者 Jiaxin Zhang Shuang Zheng Wenhao Liu 《China Communications》 SCIE CSCD 2023年第3期252-285,共34页
As a viable component of 6G wireless communication architecture,satellite-terrestrial networks support efficient file delivery by leveraging the innate broadcast ability of satellite and the enhanced powerful file tra... As a viable component of 6G wireless communication architecture,satellite-terrestrial networks support efficient file delivery by leveraging the innate broadcast ability of satellite and the enhanced powerful file transmission approaches of multi-tier terrestrial networks.In the paper,we introduce edge computing technology into the satellite-terrestrial network and propose a partition-based cache and delivery strategy to make full use of the integrated resources and reducing the backhaul load.Focusing on the interference effect from varied nodes in different geographical distances,we derive the file successful transmission probability of the typical user and by utilizing the tool of stochastic geometry.Considering the constraint of nodes cache space and file sets parameters,we propose a near-optimal partition-based cache and delivery strategy by optimizing the asymptotic successful transmission probability of the typical user.The complex nonlinear programming problem is settled by jointly utilizing standard particle-based swarm optimization(PSO)method and greedy based multiple knapsack choice problem(MKCP)optimization method.Numerical results show that compared with the terrestrial only cache strategy,Ground Popular Strategy,Satellite Popular Strategy,and Independent and identically distributed popularity strategy,the performance of the proposed scheme improve by 30.5%,9.3%,12.5%and 13.7%. 展开更多
关键词 edge computing satellite terrestrial net-works caching deployment stochastic geometry 6G networks
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Edge Computing-Based Tasks Offloading and Block Caching for Mobile Blockchain 认领 引用 被引量：3
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作者 Yong Yan Yao Dai +2 位作者 Zhiqiang Zhou Wei Jiang Shaoyong Guo 《Computers, Materials & Continua》 SCIE EI 2020年第2期905-915,共11页
Internet of Things(IoT)technology is rapidly evolving,but there is no trusted platform to protect user privacy,protect information between different IoT domains,and promote edge processing.Therefore,we integrate the b... Internet of Things(IoT)technology is rapidly evolving,but there is no trusted platform to protect user privacy,protect information between different IoT domains,and promote edge processing.Therefore,we integrate the blockchain technology into constructing trusted IoT platforms.However,the application of blockchain in IoT is hampered by the challenges posed by heavy computing processes.To solve the problem,we put forward a blockchain framework based on mobile edge computing,in which the blockchain mining tasks can be offloaded to nearby nodes or the edge computing service providers and the encrypted hashes of blocks can be cached in the edge computing service providers.Moreover,we model the process of offloading and caching to ensure that both edge nodes and edge computing service providers obtain the maximum profit based on game theory and auction theory.Finally,the proposed mechanism is compared with the centralized mode,mode A(all the miners offload their tasks to the edge computing service providers),and mode B(all the miners offload their tasks to a group of neighbor devices).Simulation results show that under our mechanism,mining networks obtain more profits and consume less time on average. 展开更多
关键词 Edge computing blockchain mining offloading block caching
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Joint Optimization of Task Caching,Computation Offloading and Resource Allocation for Mobile Edge Computing 认领 引用 被引量：2
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作者 Zhixiong Chen Zhengchuan Chen +3 位作者 Zhi Ren Liang Liang Wanli Wen Yunjian Jia 《China Communications》 SCIE CSCD 2022年第12期142-159,共18页
Applications with sensitive delay and sizeable data volumes,such as interactive gaming and augmented reality,have become popular in recent years.These applications pose a huge challenge for mobile users with limited r... Applications with sensitive delay and sizeable data volumes,such as interactive gaming and augmented reality,have become popular in recent years.These applications pose a huge challenge for mobile users with limited resources.Computation offloading is a mainstream technique to reduce execution delay and save energy for mobile users.However,computation offloading requires communication between mobile users and mobile edge computing(MEC) servers.Such a mechanism would difficultly meet users’ demand in some data-hungry and computation-intensive applications because the energy consumption and delay caused by transmissions are considerable expenses for users.Caching task data can effectively reduce the data transmissions when users offload their tasks to the MEC server.The limited caching space at the MEC server calls for judiciously decide which tasks should be cached.Motivated by this,we consider the joint optimization of computation offloading and task caching in a cellular network.In particular,it allows users to proactively cache or offload their tasks at the MEC server.The objective of this paper is to minimize the system cost,which is defined as the weighted sum of task execution delay and energy consumption for all users.Aiming at establishing optimal performance bound for the system design,we formulate an optimization problem by jointly optimizing the task caching,computation offloading,and resource allocation.The problem is a challenging mixed-integer non-linear programming problem and is NP-hard in general.To solve it efficiently,by using convex optimization,Karmarkar ’s algorithm and the proposed fast search algorithm,we obtain an optimal solution of the formulated problem with manageable computational complexity.Extensive simulation results show that in comparison to some representative benchmark methods,the proposed solution can effectively reduce the system cost. 展开更多
关键词 mobile edge computing computation offloading caching resource allocation
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Edge Computing Task Scheduling with Joint Blockchain and Task Caching in Industrial Internet 认领 引用 被引量：1
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作者 Yanping Chen Xuyang Bai +3 位作者 Xiaomin Jin Zhongmin Wang Fengwei Wang Li Ling 《Computers, Materials & Continua》 SCIE EI 2023年第4期2101-2117,共17页
Deploying task caching at edge servers has become an effectiveway to handle compute-intensive and latency-sensitive tasks on the industrialinternet. However, how to select the task scheduling location to reduce taskde... Deploying task caching at edge servers has become an effectiveway to handle compute-intensive and latency-sensitive tasks on the industrialinternet. However, how to select the task scheduling location to reduce taskdelay and cost while ensuring the data security and reliable communicationof edge computing remains a challenge. To solve this problem, this paperestablishes a task scheduling model with joint blockchain and task cachingin the industrial internet and designs a novel blockchain-assisted cachingmechanism to enhance system security. In this paper, the task schedulingproblem, which couples the task scheduling decision, task caching decision,and blockchain reward, is formulated as the minimum weighted cost problemunder delay constraints. This is a mixed integer nonlinear problem, which isproved to be nonconvex and NP-hard. To solve the optimal solution, thispaper proposes a task scheduling strategy algorithm based on an improvedgenetic algorithm (IGA-TSPA) by improving the genetic algorithm initializationand mutation operations to reduce the size of the initial solutionspace and enhance the optimal solution convergence speed. In addition,an Improved Least Frequently Used algorithm is proposed to improve thecontent hit rate. Simulation results show that IGA-TSPA has a faster optimalsolution-solving ability and shorter running time compared with the existingedge computing scheduling algorithms. The established task scheduling modelnot only saves 62.19% of system overhead consumption in comparison withlocal computing but also has great significance in protecting data security,reducing task processing delay, and reducing system cost. 展开更多
关键词 Edge computing task scheduling blockchain task caching industrial security
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SERVICES AND COMMUNICATIONS IN FOG COMPUTING 认领 引用 被引量：1
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作者 shangguang wang ao zhou +1 位作者 michael m.komarov stephen s.yau 《China Communications》 SCIE CSCD 2017年第11期I0001-I0002,共2页
In the current cloud-based Internet-of-Things （IoT） model, smart devices （such as sensors, smartphones） exchange information through the Internet to cooperate and provide services to users, which could be citizens... In the current cloud-based Internet-of-Things （IoT） model, smart devices （such as sensors, smartphones） exchange information through the Internet to cooperate and provide services to users, which could be citizens, smart home systems, and industrial applications. 展开更多
关键词 SERVICES COMMUNICATIONS FOG COMPUTING
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A Hybrid Heuristic Service Caching and Task Offloading Method for Mobile Edge Computing 认领 引用
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作者 Yongxuan Sang Jiangpo Wei +1 位作者 Zhifeng Zhang Bo Wang 《Computers, Materials & Continua》 SCIE EI 2023年第8期2483-2502,共20页
Computing-intensive and latency-sensitive user requests pose significant challenges to traditional cloud computing.In response to these challenges,mobile edge computing(MEC)has emerged as a new paradigm that extends t... Computing-intensive and latency-sensitive user requests pose significant challenges to traditional cloud computing.In response to these challenges,mobile edge computing(MEC)has emerged as a new paradigm that extends the computational,caching,and communication capabilities of cloud computing.By caching certain services on edge nodes,computational support can be provided for requests that are offloaded to the edges.However,previous studies on task offloading have generally not considered the impact of caching mechanisms and the cache space occupied by services.This oversight can lead to problems,such as high delays in task executions and invalidation of offloading decisions.To optimize task response time and ensure the availability of task offloading decisions,we investigate a task offloading method that considers caching mechanism.First,we incorporate the cache information of MEC into the model of task offloading and reduce the task offloading problem as a mixed integer nonlinear programming(MINLP)problem.Then,we propose an integer particle swarm optimization and improved genetic algorithm(IPSO_IGA)to solve the MINLP.IPSO_IGA exploits the evolutionary framework of particle swarm optimization.And it uses a crossover operator to update the positions of particles and an improved mutation operator to maintain the diversity of particles.Finally,extensive simulation experiments are conducted to evaluate the performance of the proposed algorithm.The experimental results demonstrate that IPSO_IGA can save 20%to 82%of the task completion time,compared with state-of-theart and classical algorithms.Moreover,IPSO_IGA is suitable for scenarios with complex network structures and computing-intensive tasks. 展开更多
关键词 Mobile edge computing edge caching task offloading particle swarm optimization genetic algorithm
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A Review in the Core Technologies of 5G: Device-to-Device Communication, Multi-Access Edge Computing and Network Function Virtualization 认领 引用 被引量：3
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作者 Ruixuan Tu Ruxun Xiang +1 位作者 Yang Xu Yihan Mei 《International Journal of Communications, Network and System Sciences》 2019年第9期125-150,共26页
5G is a new generation of mobile networking that aims to achieve unparalleled speed and performance. To accomplish this, three technologies, Device-to-Device communication (D2D), multi-access edge computing (MEC) and ... 5G is a new generation of mobile networking that aims to achieve unparalleled speed and performance. To accomplish this, three technologies, Device-to-Device communication (D2D), multi-access edge computing (MEC) and network function virtualization (NFV) with ClickOS, have been a significant part of 5G, and this paper mainly discusses them. D2D enables direct communication between devices without the relay of base station. In 5G, a two-tier cellular network composed of traditional cellular network system and D2D is an efficient method for realizing high-speed communication. MEC unloads work from end devices and clouds platforms to widespread nodes, and connects the nodes together with outside devices and third-party providers, in order to diminish the overloading effect on any device caused by enormous applications and improve users’ quality of experience (QoE). There is also a NFV method in order to fulfill the 5G requirements. In this part, an optimized virtual machine for middle-boxes named ClickOS is introduced, and it is evaluated in several aspects. Some middle boxes are being implemented in the ClickOS and proved to have outstanding performances. 展开更多
关键词 5th Generation Network Virtualization Device-To-Device communication Base Station Direct Communication Interference Multi-Access Edge Computing Mobile Edge Computing
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Application and Challenge of Edge Computing Based on 5G Communication in Information and Communication Systems 认领 引用 被引量：2
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作者 Zhengwei Li Kan Cao 《Journal of Electronic Research and Application》 2024年第6期39-45,共7页
With the rapid development of information technology,5G communication technology has gradually entered real life,among which the application of edge computing is particularly significant in the information and communi... With the rapid development of information technology,5G communication technology has gradually entered real life,among which the application of edge computing is particularly significant in the information and communication system field.This paper focuses on using edge computing based on 5G communication in information and communication systems.First,the study analyzes the importance of combining edge computing technology with 5G communication technology,and its advantages,such as high efficiency and low latency in processing large amounts of data.The study then explores multiple application scenarios of edge computing in information and communication systems,such as integrated use in the Internet of Things,intelligent transportation,telemedicine and Industry 4.0.The research method is mainly based on theoretical analysis and experimental verification,combined with the characteristics of the 5G network to optimize the edge computing model and test the performance of edge computing in different scenarios through experimental simulation.The results show that edge computing significantly improves the data processing capacity and response speed of ICS in a 5G environment.However,there are also a series of challenges in practical application,including data security and privacy protection,the complexity of resource management and allocation,and the guarantee of quality of service(QoS).Through the case analysis and problem analysis,the paper puts forward the corresponding solution strategies,such as strengthening the data security protocol,introducing the intelligent resource scheduling system and establishing a multi-dimensional service quality monitoring mechanism.Finally,this study points out that the deep integration of edge computing and 5G communication will continue to promote the innovative development of information and communication systems,which has a far-reaching impact and important practical significance for promoting the transformation and upgrading in the field of information technology. 展开更多
关键词 5G communication Edge computing Information communication system Data security Service quality
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Service Caching and Task Offloading for Mobile Edge Computing-Enabled Intelligent Connected Vehicles 认领 引用 被引量：4
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作者 HUANG Mengting YI Yuhan ZHANG Guanglin 《Journal of Shanghai Jiaotong university(Science)》 EI 2021年第5期670-679,共10页
The development of intelligent connected vehicles(ICVs)has tremendously inspired the emergence of a new computing paradigm called mobile edge computing(MEC),which meets the demands of delay-sensitive on-vehicle applic... The development of intelligent connected vehicles(ICVs)has tremendously inspired the emergence of a new computing paradigm called mobile edge computing(MEC),which meets the demands of delay-sensitive on-vehicle applications.Most existing studies focusing on the issue of task offloading in ICVs assume that the MEC server can directly complete computation tasks without considering the necessity of service caching.However,this is unrealistic in practice because a large number of tasks require the use of corresponding third-party libraries and databases,that is,service caching.Therefore,we investigate the delay optimization in an MEC-enabled ICVs system with multiple mobile vehicles,resource-limited base stations(BSs),and one cloud server.We aim to determine the optimal service caching and task offloading decisions to minimize the overall system delay using mixed-integer nonlinear programming.To address this problem,we first convert it into a quadratically constrained quadratic program and then propose an efficient semidefinite relaxation-based joint service caching and task offloading(JSCTO)algorithm to obtain the service caching and task offloading decisions.In the simulations,we validate the efficiency of our proposed method by setting different numbers of vehicles and the storage capacity of BSs.The results show that our proposed JSCTO algorithm can significantly decrease the total delay of all offloaded tasks compared with the cloud processing only scheme. 展开更多
关键词 intelligent connected vehicle(ICV) mobile edge computing(MEC) service caching task offloading delay cost
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Deep Reinforcement Learning-Based Task Offloading and Service Migrating Policies in Service Caching-Assisted Mobile Edge Computing 认领 引用 被引量：1
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作者 Ke Hongchang Wang Hui +1 位作者 Sun Hongbin Halvin Yang 《China Communications》 SCIE CSCD 2024年第4期88-103,共16页
Emerging mobile edge computing(MEC)is considered a feasible solution for offloading the computation-intensive request tasks generated from mobile wireless equipment(MWE)with limited computational resources and energy.... Emerging mobile edge computing(MEC)is considered a feasible solution for offloading the computation-intensive request tasks generated from mobile wireless equipment(MWE)with limited computational resources and energy.Due to the homogeneity of request tasks from one MWE during a longterm time period,it is vital to predeploy the particular service cachings required by the request tasks at the MEC server.In this paper,we model a service caching-assisted MEC framework that takes into account the constraint on the number of service cachings hosted by each edge server and the migration of request tasks from the current edge server to another edge server with service caching required by tasks.Furthermore,we propose a multiagent deep reinforcement learning-based computation offloading and task migrating decision-making scheme(MBOMS)to minimize the long-term average weighted cost.The proposed MBOMS can learn the near-optimal offloading and migrating decision-making policy by centralized training and decentralized execution.Systematic and comprehensive simulation results reveal that our proposed MBOMS can converge well after training and outperforms the other five baseline algorithms. 展开更多
关键词 deep reinforcement learning mobile edge computing service caching service migrating
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DRL-based federated self-supervised learning for task offloading and resource allocation in ISAC-enabled vehicle edge computing 认领 引用 被引量：4
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作者 Xueying Gu Qiong Wu +3 位作者 Pingyi Fan Nan Cheng Wen Chen Khaled B.Letaief 《Digital Communications and Networks》 SCIE EI CSCD 2025年第5期1614-1627,共14页
Intelligent Transportation Systems(ITS)leverage Integrated Sensing and Communications(ISAC)to enhance data exchange between vehicles and infrastructure in the Internet of Vehicles(IoV).This integration inevitably incr... Intelligent Transportation Systems(ITS)leverage Integrated Sensing and Communications(ISAC)to enhance data exchange between vehicles and infrastructure in the Internet of Vehicles(IoV).This integration inevitably increases computing demands,risking real-time system stability.Vehicle Edge Computing(VEC)addresses this by offloading tasks to Road Side Units(RSUs),ensuring timely services.Our previous work,the FLSimCo algorithm,which uses local resources for federated Self-Supervised Learning(SSL),has a limitation:vehicles often can’t complete all iteration tasks.Our improved algorithm offloads partial tasks to RSUs and optimizes energy consumption by adjusting transmission power,CPU frequency,and task assignment ratios,balancing local and RSU-based training.Meanwhile,setting an offloading threshold further prevents inefficiencies.Simulation results show that the enhanced algorithm reduces energy consumption and improves offloading efficiency and accuracy of federated SSL. 展开更多
关键词 Integrated sensing and communications(ISAC) Federated self-supervised learning Resource allocation and offloading Deep reinforcement learning(DRL) Vehicle edge computing(VEC)
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Convergence of computing,communication,and caching in internet of things 认领 引用 被引量：5
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作者 Mohammed Amine Bouras Fadi Farha Huansheng Ning 《Intelligent and Converged Networks》 EI 2020年第1期18-36,共19页
Internet of Things(IoTs)is a big world of connected objects,including the small and low-resources devices,like sensors,as well as the full-functional computing devices,such as servers and routers in the core network.W... Internet of Things(IoTs)is a big world of connected objects,including the small and low-resources devices,like sensors,as well as the full-functional computing devices,such as servers and routers in the core network.With the emerging of new IoT-based applications,such as smart transportation,smart agriculture,healthcare,and others,there is a need for making great efforts to achieve a balance in using the IoT resources,including Computing,Communication,and Caching.This paper provides an overview of the convergence of Computing,Communication,and Caching(CCC)by covering the IoT technology trends.At first,we give a snapshot of technology trends in communication,computing,and caching.As well,we describe the convergence in sensors,devices,and gateways.Addressing the aspect of convergence,we discuss the relationship between CCC technologies in collecting,indexing,processing,and storing data in IoT.Also,we introduce the three dimensions of the IoTs based on CCC.We explore different existing technologies that help to solve bottlenecks caused by a large number of physical devices in IoT.Finally,we propose future research directions and open problems in the convergence of communication,computing,and cashing with sensing and actuating devices. 展开更多
关键词 convergence computing communication caching sensing actuating Internet of Things(IoTs)
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